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INFORMATICALT
2008
196views more  INFORMATICALT 2008»
13 years 7 months ago
An Efficient and Sensitive Decision Tree Approach to Mining Concept-Drifting Data Streams
Abstract. Data stream mining has become a novel research topic of growing interest in knowledge discovery. Most proposed algorithms for data stream mining assume that each data blo...
Cheng-Jung Tsai, Chien-I Lee, Wei-Pang Yang
DAWAK
2005
Springer
14 years 16 days ago
Processing Sequential Patterns in Relational Databases
Database integration of data mining has gained popularity and its significance is well recognized. However, the performance of SQL based data mining is known to fall behind specia...
Xuequn Shang, Kai-Uwe Sattler
ICTAI
2006
IEEE
14 years 1 months ago
Sequence Mining Without Sequences: A New Way for Privacy Preserving
During the last decade, sequential pattern mining has been the core of numerous researches. It is now possible to efficiently discover users’ behavior in various domains such a...
Stéphanie Jacquemont, François Jacqu...
DATAMINE
2006
142views more  DATAMINE 2006»
13 years 7 months ago
Sequential Pattern Mining in Multi-Databases via Multiple Alignment
To efficiently find global patterns from a multi-database, information in each local database must first be mined and summarized at the local level. Then only the summarized infor...
Hye-Chung Kum, Joong Hyuk Chang, Wei Wang 0010
CIS
2004
Springer
14 years 12 days ago
Knowledge Maintenance on Data Streams with Concept Drifting
Concept drifting in data streams often occurs unpredictably at any time. Currently many classification mining algorithms deal with this problem by using an incremental learning ap...
Juggapong Natwichai, Xue Li